This work introduces some of the most widely usedcompression algorithms, and their relevance to the field oflivestock farming, which has been historically characterizedfor requiring menial and inefficient labor, introducingenvironmental. And also for lacking the scale andautomation that cutting edge technologies can provide. Bydoing this we will explain how this opens the door tolocations untouched by technology, and the generaladvantages, and possibilities that integrating patternrecognition models bring to the table. In addition, we willexplain the ins and outs of these compression algorithms,and our reasoning behind our decision to choose analgorithm to implement in our pattern recognition model.To solve this problem, Seam Carving, Image Scaling andRun-Length encoding were used. With them we compressedthe images an average of 17.5% of their original size in atime complexity of O(L*N*M). This research shows howyou can create an efficient compression algorithm for usagein PLF.